Positively skewed data: revisiting the box-cox power transformation.

Although the normal probability distribution is the cornerstone of applying statistical methodology; data do not always meet the necessary normal distribution assumptions. In these cases, researchers often transform non-normal data to a distribution that is approximately normal. Power transformation...

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Autores principales:	Jake Olivier, Melissa M. Norberg
Formato:	article
Lenguaje:	EN ES
Publicado:	Universidad de San Buenaventura 2010
Materias:	Logarithmic transformations geometric mean analysis ex-Gaussian distribution log-normal distribution Psychology BF1-990
Acceso en línea:	https://doaj.org/article/ff8ff67de3c34cf1a06984deb4592c13
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id	oai:doaj.org-article:ff8ff67de3c34cf1a06984deb4592c13
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spelling	oai:doaj.org-article:ff8ff67de3c34cf1a06984deb4592c132021-11-25T02:24:04ZPositively skewed data: revisiting the box-cox power transformation.10.21500/20112084.8462011-20842011-7922https://doaj.org/article/ff8ff67de3c34cf1a06984deb4592c132010-06-01T00:00:00Zhttps://revistas.usb.edu.co/index.php/IJPR/article/view/846https://doaj.org/toc/2011-2084https://doaj.org/toc/2011-7922Although the normal probability distribution is the cornerstone of applying statistical methodology; data do not always meet the necessary normal distribution assumptions. In these cases, researchers often transform non-normal data to a distribution that is approximately normal. Power transformations constitute a family of transformations, which include logarithmic and fractional exponent transforms. The Box-Cox method offers a simple method for choosing the most appropriate power transformation. Another option for data that is positively skewed, often used when measuring reaction times, is the Ex-Gaussian distribution which is a combination of the exponential and normal distributions. In this paper, the Box-Cox power transformation and Ex-Gaussian distribution will be discussed and compared in the context of positively skewed data. This discussion will demonstrate that the Box-Cox power transformation is simpler to apply and easier to interpret than the Ex-Gaussian distribution.Jake OlivierMelissa M. NorbergUniversidad de San BuenaventuraarticleLogarithmic transformationsgeometric mean analysisex-Gaussian distributionlog-normal distributionPsychologyBF1-990ENESInternational Journal of Psychological Research, Vol 3, Iss 1 (2010)
institution	DOAJ
collection	DOAJ
language	EN ES
topic	Logarithmic transformations geometric mean analysis ex-Gaussian distribution log-normal distribution Psychology BF1-990
spellingShingle	Logarithmic transformations geometric mean analysis ex-Gaussian distribution log-normal distribution Psychology BF1-990 Jake Olivier Melissa M. Norberg Positively skewed data: revisiting the box-cox power transformation.
description	Although the normal probability distribution is the cornerstone of applying statistical methodology; data do not always meet the necessary normal distribution assumptions. In these cases, researchers often transform non-normal data to a distribution that is approximately normal. Power transformations constitute a family of transformations, which include logarithmic and fractional exponent transforms. The Box-Cox method offers a simple method for choosing the most appropriate power transformation. Another option for data that is positively skewed, often used when measuring reaction times, is the Ex-Gaussian distribution which is a combination of the exponential and normal distributions. In this paper, the Box-Cox power transformation and Ex-Gaussian distribution will be discussed and compared in the context of positively skewed data. This discussion will demonstrate that the Box-Cox power transformation is simpler to apply and easier to interpret than the Ex-Gaussian distribution.
format	article
author	Jake Olivier Melissa M. Norberg
author_facet	Jake Olivier Melissa M. Norberg
author_sort	Jake Olivier
title	Positively skewed data: revisiting the box-cox power transformation.
title_short	Positively skewed data: revisiting the box-cox power transformation.
title_full	Positively skewed data: revisiting the box-cox power transformation.
title_fullStr	Positively skewed data: revisiting the box-cox power transformation.
title_full_unstemmed	Positively skewed data: revisiting the box-cox power transformation.
title_sort	positively skewed data: revisiting the box-cox power transformation.
publisher	Universidad de San Buenaventura
publishDate	2010
url	https://doaj.org/article/ff8ff67de3c34cf1a06984deb4592c13
work_keys_str_mv	AT jakeolivier positivelyskeweddatarevisitingtheboxcoxpowertransformation AT melissamnorberg positivelyskeweddatarevisitingtheboxcoxpowertransformation
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Positively skewed data: revisiting the box-cox power transformation.

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